The tuning of a fuzzy model is discussed in the context of choices made between different t-norms. The effects of the choice is illustrated by looking at two fuzzy models initially generated, respectively, by grid partition and a novel variant of subtractive clustering. The new variant of subtractiv
Mountain and subtractive clustering method: Improvements and generalizations
β Scribed by Nikhil R. Pal; Debrup Chakraborty
- Publisher
- John Wiley and Sons
- Year
- 2000
- Tongue
- English
- Weight
- 225 KB
- Volume
- 15
- Category
- Article
- ISSN
- 0884-8173
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β¦ Synopsis
The mountain method of clustering and its relative, the subtractive clustering method, are studied here. A scheme to improve the accuracy of the prototypes obtained by the mountain method is proposed. Finally the mountain circular shell method to detect circular shells by using the mountain function is proposed. The proposed method is tested extensively on several synthetic data sets, and the results obtained are quite satisfactory.
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